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Battery technology has dramatically advanced over a decade and many high performance batteries are being developed. Electric vehicles (EV) require high power batteries with suitable battery management systems (BMS) for safe and reliable operations. Intention of this paper is to discuss about the batteries used in electric vehicles and the key issue...
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... popular types of batteries are Dry cell, Alkaline cell, lithium-ion (Li-ion), lead-acid (PbA), Nickel-Cadmium (NiCd), Nickel-Metal Hydride (NiMH), Nickel Zinc, Zinc air.as shown in Table 1 with their electrochemistry. Among the above different types of batteries, NiMH and Li-ion batteries are highly preferred. ...Similar publications
With the development of electric vehicles in China, the fault monitoring and warning systems for the charging process of electric vehicles have received the industry’s attention. A method for the monitoring and warning of electric vehicle charging faults based on a battery model is proposed in this paper. Through online estimation of the state of c...
In this article, we present the datasets collected from nine different Li-ion batteries. These datasets contain voltage, current and time measurements during a full charge-discharge cycle of a battery at very low current (that is nearly at C/30 rate). Such low current rate data is suitable for open circuit voltage characterization. The collection o...
An active balancing method based on the state of charge (SOC) and capacitance is presented in this article to solve the inconsistency problem of lithium-ion batteries in electric vehicles. The terminal voltage of each battery is collected first. Then, each battery SOC is accurately estimated by an extended Kalman filter (EKF) algorithm. In the expe...
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... Esta configuración es ideal para aplicaciones que requieren mayores tensiones sin incrementar la capacidad de corriente, como en sistemas de tracción eléctrica o bancos de baterías para energía renovable. En la figura 2 se muestra la conexión en serie de tres de celdas de 3V y 20Ah [11]. Al conectar celdas en paralelo, el voltaje de la batería se mantiene igual al de una sola celda, mientras que la capacidad total se convierte en la suma de las capacidades individuales. ...
... Los componentes claves incluyen: elánodo, el cátodo, el electrolito que permite el flujo iónico, el separador que evita cortocircuitos entre los electrodos, y los colectores de corriente que conectan los electrodos al circuito externo. Estos elementos trabajan en conjunto para permitir las reacciones de oxido -reducción (redox) que generan energía eléctrica [11]. En una celda electroquímica, elánodo está compuesto por un metal, una aleación o incluso hidrógeno. ...
El desarrollo de los vehículos eléctricos (VE) ha impulsado la evolución de diversas tecnologías de celdas de baterías, cada una con característicasúnicas en términos de densidad energética, vidaútil, seguridad y costos. Este artículo presenta una revisión técnica exhaustiva de los principales tipos de celdas utilizadas en VE, incluyendo las de ión-litio (Li-ion) en sus variantes NMC, LFP y LCO, así como tecnologías emergentes como las baterías de estado sólido y las de metal-aire. Se analizan sus principios electroquímicos, ventajas y limitaciones, destacando cómo la selección de la química de la celda impacta directamente en el rendimiento del vehículo. Además, se explora la relación crítica entre estas celdas y los Sistemas de Gestión de Baterías (BMS), enfatizando cómo el BMS debe adaptarse para monitorear y controlar eficientemente parámetros como el voltaje, la temperatura y el estado de carga (SOC) en cada tecnología. Finalmente, se discuten los desafíos futuros y las tendencias en el diseño de celdas y BMS para satisfacer las demandas de la movilidad sostenible. Index Terms-Baterías para vehículos eléctricos, celdas Li-ion, estado sólido, BMS, gestión térmica, densidad energética. I. INTRODUCCIÓN El crecimiento de la población y la economía global au-mentarán la demanda de energía. Según la Asociación In-ternacional de la Energía (AIE), el consumo de energía se incrementará en un 50% para 2025 respecto a 2005, lo cual es equivalente al uso de 15 millones de Toneladas de Petroleo (TEP) [1]. Este incremento será más acentuado en países en vías de desarrollo y no miembros de la Organización para la Cooperación y el Desarrollo Económicos (OCDE). Aunque los combustibles fósiles seguirán dominando, se espera un leve descenso en el consumo de petróleo, favoreciendo el empleo de las energías renovables. Los motores de combustión interna dependen de los combustibles fósiles, pero el agotamiento de estos recursos, en conjunto con las crisis económicas y geopolíticas a nivel global, generan un panorama de alta volatilidad. Además, el transporte representa entre el 23 y el 26% de las emisiones de gases de efecto invernadero a nivel global [3]. Aunque las normativas han reducido las emisiones de CO2 a 120 g CO2/km (un 25% menos), el sector crece un 30% anual, haciendo insuficientes las medidas adoptadas por las normas [2]. Por ello, se requiere un sistema de transporte más sostenible. La sostenibilidad global del sistema de transporte actual es precaria en el largo plazo. Según las proyecciones, la depen-dencia del petróleo en este sector se mantendría por encima del 90% en las próximas décadas, con una pequeña contribución de las energías renovables que apenas lograría superar el 10% fijado como objetivo para el año 2020. Si la tendencia continua de esta manera, las emisiones de CO2 producidas por los sistemas de transporte en 2050 seguirán siendo un 33% mayores que los niveles de 1990, acentuando aún más la crisis climática global. Además, los costos asociados a la congestión vehicular se elevarían hasta en un 50% para mediados del siglo XXI [4]. Los vehículos eléctricos aminoran las emisiones de gases de efecto invernadero en proporciones variables según la matriz energética de cada país. En Estados Unidos las reducciones oscilan entre un 20 y un 50%, dependiendo de la proporción de carbón, gas natural y renovables [4]. Países con predominio de energía nuclear alcanzan reducciones de hasta 90%, mientras que en Colombia las reducciones podrían superar el 60% gracias a que su base de generación de energía eléctrica está fundamentada en hidroeléctricas (70%) y el creciente aporte de fuentes renovables no convencionales [5]. El transporte sostenible, impulsado por vehículos de combustibles alter-nativos como automóviles y motocicletas eléctricas, se ha consolidado como una estrategia clave en las políticas de movilidad de diversos países [6]. No obstante, la adopción generalizada de Vehículos Eléctricos (VE) y su desarrollo a gran escala requieren el diseño e implementación de una infraestructura adecuada que garantice servicios de recarga accesibles para los futuros usuarios [7]. La recarga de VE se realiza en entornos diferentes, tales como parqueaderos y garajes de conjuntos residenciales de-bido a factores como la alta concentración de usuarios, las demandas variables de potencia y tiempo de carga, las llegadas aleatorias de vehículos, las limitaciones de potencia con-tratada y la necesidad de sistemas de gestión inteligente. Las características de los cargadores anteriormente mencionadas
... Similar characteristics of NiMH and Li-ions are compared and analyzed in the paper [44]. Parameters such as open circuit voltage, SOC, aging, and temperature management were studied. ...
Electric vehicles (EVs) are a promising zero-emission technology in the automobile industry, but they face several challenges in terms of performance, reliability, and safety. Batteries are the heart of the EV system which helps to run the vehicle with reliability. Batteries during the process of running undergo various changes that need to be addressed. On the other hand, real-time data analysis and online access to information are necessary conditions in the modern world. Machine learning and deep learning algorithms mimic humans by focusing on statistical data and algorithms on a real-time basis. Terefore, in today's research, machine learning and deep learning algorithms are used in EV technologies to obtain a more efcient and capable system. Te battery management system (BMS) is the main part that is often in need of data processing of battery parameters and diagnosis of the problem. Tis paper explores the comprehensive literature review on machine learning and deep learning approaches for BMS in EVs. Te state of charge (SOC) estimation, charge equalization and cell balancing, fault detection and diagnosis, and thermal management systems using various combined machine learning and deep learning techniques are discussed. By synthesizing insights from various studies, this article presents improved parameters and valuable inferences. Tis article aims to highlight the pivotal role of artifcial intelligence (AI) and deep learning in improving the functionality of the BMS, ultimately contributing to the performance and longevity of EVs.
... The study of battery operation and its input-output characteristics can be facilitated by the use of battery modeling. In order to get a well-designed BMS that effectively controls and optimizes battery performance, it is imperative to utilize an appropriate battery model [15]. Cell balance is yet another useful function provided by BMS. ...
Electric vehicles and hybrid electric vehicles (EV) are increasingly common on roads today compared to a decade ago, driven by advancements in technology and a growing focus on sustainable transportation. These vehicles are powered by rechargeable lithium-ion batteries. A battery management system (BMS) is indispensable for ensuring the optimal performance, safety, and longevity of the EV’s batteries. In this review, the latest algorithm trends for BMS software are discussed. This work also focuses on several key functionalities of BMS like the state of charge (SOC) estimation, state of health (SOH) monitoring, state of energy (SOE), and state of power (SOP). Advanced algorithms for BMS are comprehensively reviewed, including those designed for specific functionalities, as well as those developed based on existing optimization, artificial intelligence, and estimation algorithms. These algorithms address critical challenges such as maintaining symmetry during charging and discharging, preventing thermal runaway, and managing battery faults in EV systems. This work provides valuable insights for researchers and practitioners in the field of EV design and development, particularly those focusing on the advancement of BMS technologies.
... The MatLab/Simulink software package provides a wide range of tools and block libraries for modelling various systems and processes with high accuracy [17][18][19][20]. The performance and the range of all-electric snowmobile can be estimated by applying different driving cycles and external conditions [21][22][23][24]. ...
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
... Similar cost, life cycle, energy density, power density, and efficiency of lead-acid, nickel cadmium, and lithium-ion batteries are compared in [31], listing lithium-ion as the best performing at the expense of cost. 60-150 [29] 40-80 [32] 65-75 [20] 20-35 [33] 200-400 [29] 140-300 [29] 160-275 [29] 25-33 [29] 55-65 [29] Power Density (W/L) 10-400 [29] 80-600 [29] 250-1000 [34] 60-110 [20] 70-100 [33] 1500-10,000 [29] 140-300 [29] 150-270 [29] 1-2 [29] 1-25 [29] Cell Nominal Voltage (V) 2 [29] 1.3 [29] 1.2 [32] 1.67 [33] 1.18 [33] 4.3 [29] 2.08 [29] 2.85-3.1 [35] 1.4 [29] 1.8 [29] Round 100% [29] 100% [29] 100% [29] 100% [29] Operating Temperature −20-60 [33] −40-60 [33] −20-60 [33] −20-60 [33] −40-60 [33] −20-60 [33] 300-350 [36] −70-100 [37] 10-40 [ Life Cycle 1500 [29] 2500 [29] 800-1200 [32] 200-400 [20] 300 [43] 10,000 [29] 5000 [29] 3000 [29] 13,000 [29] 10,000 [29] Estimated Cost (USD/kWh) 105-475 [29] 400 100-500 170-580 290 200-1260 [29] 263-735 [29] 315-488 [29] 315-1050 [29] 525-1680 [29] Lithium battery research [44] started in 1912, long before lithium-ion batteries became prominent in 1976 [20]. By that time, metallic lithium anodes and nonaqueous electrolytes were employed in the initial lithium-metal batteries (LMBs), resulting in substantial enhancements in specific energy and energy density. ...
... Energies 2024, 17, 323 ...
The growing number of electric vehicles and devices drives the demand for lithium-ion batteries. The purpose of the batteries used in electric vehicles and applications is primarily to preserve the cells and extend their lifetime, but they will wear out over time, even under ideal conditions. Most battery system failures are caused by a few cells, but the entire system may have to be scrapped in such cases. To address this issue, the goal is to create a concept that will extend the life of batteries while reducing the industrial and chemical waste generated by batteries. Secondary use can increase battery utilization and extend battery life. However, processing a large number of used battery cells at an industrial level is a significant challenge for both manufacturers and users. The different battery sizes and compositions used by various manufacturers of electric vehicles and electronic devices make it extremely difficult to solve the processing problem at the system level. The purpose of this study is to look into non-destructive battery diagnostic options. During the tests, the condition of the cells is assessed using a new diagnostic technique, 3D surface digitalization, and the fusion of electrical parameters. In the case of surface digitalization, the digital image correlation (DIC) technique was used to estimate the cell state. The tests were conducted on various cells with widely used geometries and encapsulations. These included a lithium polymer (soft casing), 18650 standard sizes (hard casing), and prismatic cells (semi-hard). The study also included testing each battery at various charge states during charging and discharging. The findings help to clarify the changes in battery cell geometry and their localization. The findings can be applied to cell diagnostic applications such as recycling, quality assurance, and vehicle diagnostics.
... Despite the promising advancements in Battery Management Systems (BMS), several challenges persist, particularly concerning the efficiency and effectiveness of energy storage solutions (Habib et al., 2023). One of the notable issues is the failure to achieve optimal energy conversion rates in many existing BMS (Karkuzhali et al., 2020). Energy conversion efficiency is crucial in determining how effectively energy can be stored and subsequently, retrieved from batteries (Magsumbol et al., 2022). ...
This paper presents an innovative approach to developing enhanced Battery Management Systems (BMS) tailored for sustainable energy applications in Namibia. As the country transitions towards increased renewable energy integration, efficient energy storage solutions are crucial for maintaining system stability and reliability. We propose a comprehensive BMS framework that addresses the unique challenges posed by Namibia's climatic and infrastructural conditions. Our approach incorporates advanced algorithms for optimizing battery performance, predictive maintenance, and real-time monitoring, all while ensuring minimal energy losses and extended battery life. Through simulations and field trials, we demonstrate the system's effectiveness in improving energy management and reducing operational costs. The findings indicate that our enhanced BMS significantly contributes to the efficiency and sustainability of energy use in Namibia, paving the way for a more resilient and eco-friendly energy infrastructure.
... Fitur pada BMS seperti pemodelan baterai, estimasi status baterai, pengisian daya dan pemakaian daya. Dengan adanya BMS, diharapkan dapat mendeteksi kondisi tidak aman pada baterai, melindungi baterai dari kerusakan saat terjadi kegagalan dan memperpanjang umur baterai [4]. ...
Semakin pentingnya baterai yang digunakan dalam kehidupan sehari-hari termasuk dalam kelistrikan fasilitas operasi perkeretaapian, serta untuk menjaga kualitas dan keandalan baterai, menyebabkan Battery Management System (BMS) sangat diperlukan. BMS dapat digunakan untuk menghindari over charge, short circuit dan suhu ekstrim pada baterai. Tujuan dari perancangan prototipe BMS ini yaitu untuk memonitoring nilai SOC dan SOH baterai secara real time. Nilai SOC dihitung dengan metode Open Circuit Voltage (OCV) dan metode Coloumb Counting (CC). Sedangkan nilai SOH dihitung dengan membandingkan muatan saat ini dan muatan kondisi baru. Pada prototipe BMS, sensor pembagi tegangan, sensor arus dan sensor suhu dihubungkan pada baterai. Data dari ketiga sensor tersebut akan diolah dengan Arduino dan dikirim ke software LabView. LabView akan menampilkan nilai tegangan, arus, suhu, SOC dan SOH baterai. Dari hasil pengujian menggunakan jenis baterai baru dan lama, komponen sensor BMS berfungsi dengan akurasi yang tinggi. Baterai baru memiliki kinerja pengisian dan pengosongan yang lebih baik daripada baterai lama. Baterai lama juga memiliki suhu yang lebih panas dibandingkan dengan baterai baru. Oleh karena itu, BMS sangat diperlukan untuk menjaga kondisi baterai agar bekerja dengan baik. ABSTRACT The increasing importance of the battery used in everyday life include in the railway electrical operation facility, as well as to maintain the quality and reliability of the battery, makes a Battery Management System (BMS) indispensable. BMS can be used to avoid overcharging, short circuits, and extreme temperatures on batteries. The purpose of designing this BMS prototype is to monitor the SOC and SOH values of the battery in real-time. The SOC value is calculated using the Open Circuit Voltage (OCV) method and the Columb Counting (CC) method. Meanwhile, the SOH value is calculated by comparing the current load and the new condition load. In the BMS prototype, the voltage divider sensor, current sensor, and temperature sensor are connected to the battery. Data from the three sensors will be processed by Arduino and sent to the LabView software. LabView will display the battery's voltage, current, temperature, SOC, and SOH values. From the test results using old and new batteries, the BMS sensor components function with high accuracy. New batteries have better charge and discharge performance than old batteries. Old batteries also have a hotter temperature than new batteries. Therefore, BMS is needed to maintain the condition of the battery so that it works properly. 1 PENDAHULUAN Baterai merupakan sel elektrokimia yang mengubah energi kimia menjadi energi listrik [1]. Baterai memegang peran penting dalam penyimpanan energi dalam berbagai macam penerapan [2]. Sistem kelistrikan skala besar seperti gardu induk, baterai memberikan energi listrik untuk peralatan kontrol gardu induk [1]. Sedangkan pada komponen elektronik lainnya, baterai digunakan sebagai sumber energi untuk ponsel, laptop, kamera dan perangkat medis [3]. Seiring dengan pentingnya baterai, maka untuk menjaga kualitas dan keandalan baterai, saat ini Battery Management System (BMS) sangat diperlukan. Hal ini diperlukan untuk menghindari over charge, over discharge, over current, short circuit dan suhu ekstrim pada baterai. Fitur pada BMS seperti pemodelan baterai, estimasi status baterai, pengisian daya dan pemakaian daya. Dengan adanya BMS, diharapkan dapat mendeteksi kondisi tidak aman pada baterai, melindungi baterai dari kerusakan saat terjadi kegagalan dan memperpanjang umur baterai [4]. Beberapa permasalahan pada sistem kelistrikan karena gangguan baterai terjadi pada sektor industri. Salah satu permasalahan tersebut yaitu pada tahun 2023, baterai pada UPS Stasiun Fatmawati PT. MRT Jakarta mengalami under voltage (terukur 6 Volt), yang seharusnya 12 Volt. Pada sistem kelistrikan PT. MRT Jakarta tersebut belum memiliki BMS. Untuk menjaga performa baterai, BMS diperlukan dengan menentukan perhitungan nilai State of Charge (SOC) dan State of
... A BMS (Battery Management System) is a device that monitors the voltage and current of a battery and balances the battery pack to prevent it from harm [15]. A good BMS should protect the driver/operator by detecting unsafe operating situations, protecting the cells from harm in failure cases, extending the battery's life in normal operating settings, and informing the user about the battery's details and operational status [18]. ...
The depletion of fossil fuel sources and the increasing environmental pollution caused by the burning of motor vehicle fuels are major problems worldwide that need to be solved. One of the promising solutions to overcome energy security and environmental pollution is the use of electric vehicles. E-bikes are one of the most popular electric vehicles because of their many benefits. A valve-regulated lead acid battery (VRLA) is now the most common energy source for electric vehicles. It is heavy and unsafe for the user due to its poor energy density. Lithium ion batteries may be a feasible solution. One type of Li-ion battery that is environmentally friendly is lithium ferro phosphate (LFP). The potential that exists encourages researchers to conduct research and compare the performance of VRLA batteries with LFP batteries. The data retrieval method is carried out using the Arduino data logger application and is equipped with a microcontroller to read current and voltage. The test results prove that the LFP battery has good voltage stability. The distance that can be traveled is quite long, which is up to 50.16 km, because it is supported by a large capacity. On the other hand, VRLA can only travel 37.83 kilometers. Furthermore, the energy density of LFP batteries is great. The VRLA battery has a low energy density of 38.7 Wh/kg, whereas the LFP battery has a higher energy density of 117 Wh/kg, making it lighter and safer for users.
